The present invention relates to a hard input soft output (HISO) receiver for generating a soft decision signal from a hard decision signal in a receiver system.
In the prior art, in a wired or wireless communication system, a receiver system may be a hard output receiver or soft output receiver, which checks each bit in a sequence of received signals and generates a hard decision value or soft decision value for the received bit. The receiver system further includes a soft input or hard input error correction code (ECC) decoder, which corrects errors using a decoding algorithm that corresponds to the bit decision value (hard decision value or soft decision value) output from the receiver.
FIG. 1 is a schematic circuit block diagram of a prior art receiver system 100 that uses a hard input ECC decoder 140. The receiver system 100 includes a limiter amplifier 110, a hard output (HO) receiver 120, a hard input hard output (HIHO) receiver 130, and the hard input ECC decoder 140. The receiver system 100 receives a signal Rx transmitted from a transmitter (not shown) over a wired or wireless communication channel. Then, the receiver system 100 amplifies the received signal Rx to a fixed amplitude value with the limiter amplifier 110. The Ho receiver 120 uses a threshold value to determine the reception level of the amplified signal Rx to generate a hard decision signal Sh.
The HIHO receiver 130 estimates, based on the hard decision signal Sh, the sign (+1 or −1) of each bit yk in a reception signal sequence y (y={y1, y2, . . . yN}) to generate a bit estimate value euk. Specifically, for a hard decision signal Sh corresponding to bit yk, the HIHO receiver 130 obtains a plurality of oversampling bits by asynchronously oversampling, for example, 8 or 16 samples per bit. This improves the bit error rate (BER) caused by the influence of additive white Gaussian noise (AWGN), which is added to the reception signals Rx in the communication channel. The HIHO receiver 130 then calculates from the plurality of obtained oversampling bits the Hamming distance Dh of the sample sequence through reciprocal operations of an adder 132 and a bit counter 134. Further, the HIHO receiver 130 calculates the bit estimate value euk based on the Hamming distance Dh with a hard decision circuit 136.
The ECC decoder 140 performs error correction on bit yk using the bit estimate value euk, that is, the hard decision value output from the HIHO receiver 130. In this case, the error correction mechanism implemented by the ECC decoder 140 may be, for example, a maximum likelihood decoding (MLD) scheme that uses a hard decision Viterbi, a boundary distance decoding (BDD) scheme, or the like. In the boundary distance decoding scheme, an error correction code, such as Hamming, Reed/Solomon, Bose Chaudhuri-Hocquenghem (BCH), or the like, is used.
A decoding algorithm that uses a hard decision value, such as that of the receiver system 100 of FIG. 1 is problematic inasmuch as there is a limit to the error correction capability due to the signal-to-noise ratio and bit error ratio. Although the redundant bits may be increased to improve the error correction capability, this would lower the coding efficiency. Accordingly, to apply the receiver system to a high-speed error correction device, the use of a soft input ECC decoder that performs error correction using soft decision values, which are more accurate than hard decision values, has been proposed.
FIG. 2 is a schematic block circuit diagram of a prior art receiver system 200 that includes a soft input ECC decoder 240. The receiver system 200 includes an AGC amplifier 210, a soft output (SO) receiver 220, soft input soft output (SISO) receiver 230, and the ECC decoder 240.
The SO receiver 220 includes an analog-to-digital converter (ADC) 222, which determines the reception level of a signal RX amplified by the. AGC amplifier 210 and converts the analog reception signal Rx to a digital value (reception signal sequence y, where y={y1, y2, . . . yN}). Preferably, the ADC 222 has an AD conversion capability of six bits or greater to ensure high level error correction. The digital signal value output from the ADC 222, that is, each bit yk of the reception signal sequence y, corresponds to a soft decision value.
The SISO receiver 230 calculates a log-likelihood ratio (LLR) Lcyk, which represents the logarithmic ratio of the probability that the received bit yk is +1 or −1, based on the output signal of the ADC 222 and the gain (as required) of the AGC amplifier 210. Specifically, the SISO receiver 230 calculates the Euclidean distance of the bit yk and the estimate value of the bit yk using a Euclidean distance calculator 232. Further, the SISO receiver 230 uses a CSI (Channel State Information) calculator 234 to calculate the S/N ratio, or channel state information Lc indicating the quality of the communication channel. Then, the SISO receiver 230 uses a multiplier 236 to multiply the calculated Euclidean distance by the channel state information Lc and obtain the LLR (Lcyk), which is represented by equation 1 shown below. The LLR (Lcyk) represents the sign and absolute value of the bit yk.
                                          L            c                    ⁢                      y            k                          =                              ln            ⁡                          (                                                P                  ⁡                                      (                                                                                            y                          k                                                |                                                  u                          k                                                                    =                                              +                        1                                                              )                                                                    P                  ⁡                                      (                                                                                            y                          k                                                |                                                  u                          k                                                                    =                                              -                        1                                                              )                                                              )                                =                                    ln              (                                                exp                  (                                      -                                                                                            (                                                                                    y                              k                                                        -                            m                                                    )                                                2                                                                    2                        ⁢                                                  σ                          2                                                                                                      )                                                  exp                  (                                      -                                                                                            (                                                                                    y                              k                                                        +                            m                                                    )                                                2                                                                    2                        ⁢                                                  σ                          2                                                                                                      )                                            )                        =                                                            -                                                                                    (                                                                              y                            k                                                    -                          m                                                )                                            2                                                              2                      ⁢                                              σ                        2                                                                                            +                                                                            (                                                                        y                          k                                                +                        m                                            )                                        2                                                        2                    ⁢                                          σ                      2                                                                                  =                                                                                          2                      ⁢                      m                                                              σ                      2                                                        ⁢                                      y                    k                                                  =                                                                            2                      ⁢                                              m                        2                                                                                    σ                      2                                                        ⁢                                      y                    nk                                                                                                          Equation        ⁢                                  ⁢        1            
In equation 1, P(yk|uk=+1) represents the probability of bit yk being received when “+1” symbol data uk is transmitted. P(yk|uk=−1) represents the probability of bit yk being received when “−1” symbol data uk is transmitted. In the equation, “m” represents the average value of bit yk, “σ2” represents the variance value of bit yk, that is, the transmission noise. “ynk” is the value of bit yk standardized by the average value m and represented by ynk=yk/m.
The soft input ECC decoder 240 performs error correction of the bit yk using the LLR (Lcyk), that is, a soft decision value output from the SISO receiver 230. In this case, the error correction mechanism that may be implemented by the ECC decoder 240 is, for example, the maximum likelihood decoding scheme using the soft decision Viterbi. The error correction mechanism may also be turbo decoding or low density parity check (LDPC) that performs repetitive decoding using maximum a posteriori probability (MAP) decoding or belief propagation decoding (BPD).
The receiver system 200 that uses the SISO receiver 230 requires a high performance ADC 222 (for example, ADC of six bits or eight bits or more) to ensure a high level of error correction capability and the AGC amplifier 210 to provide the ADC 222 with a signal having an appropriate level. This increases the product cost as compared to the receiver system 100 (FIG. 1). Large-scale modification is also required when the soft input ECC decoder 240 shown in FIG. 2 is applied to the receiver system 100. Such modification increases design costs and prolongs development time. Accordingly, it is desired that a receiver system capable of using a soft input ECC decoder without an ADC and an AGC amplifier be developed.